000 | 03596nam a22005655i 4500 | ||
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001 | 978-3-031-16704-1 | ||
003 | DE-He213 | ||
005 | 20240423125121.0 | ||
007 | cr nn 008mamaa | ||
008 | 221107s2022 sz | s |||| 0|eng d | ||
020 |
_a9783031167041 _9978-3-031-16704-1 |
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024 | 7 |
_a10.1007/978-3-031-16704-1 _2doi |
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050 | 4 | _aHF54.5-.56 | |
072 | 7 |
_aKJQ _2bicssc |
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072 | 7 |
_aCOM039000 _2bisacsh |
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072 | 7 |
_aKJQ _2thema |
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082 | 0 | 4 |
_a658.4038 _223 |
100 | 1 |
_aPincay Nieves, Jhonny. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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245 | 1 | 0 |
_aSmart Urban Logistics _h[electronic resource] : _bImproving Delivery Services by Computational Intelligence / _cby Jhonny Pincay Nieves. |
250 | _a1st ed. 2022. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2022. |
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300 |
_aXXIII, 170 p. 1 illus. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aFuzzy Management Methods, _x2196-4149 |
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505 | 0 | _aPart I. Motivation & Objectives -- Chapter 1. Introduction -- Part II. Theoretical Background -- Chapter 2. Insights into Smart Cities and Smart Logistics -- Chapter 3. Computational Intelligence -- Part III. Applications -- Chapter 4. Fuzzifying Geospatial Traffic Data to Convey Information -- Chapter 5. Ethical Classification of Postal Customers -- Part IV. Framework and Implementation -- Chapter 6. The Fuzzy Ant Routing (FAR) Conceptual Framework -- Chapter 7. The FAR Artifact -- Part V. Conclusions -- Chapter 8. Outlook and Conclusions. | |
520 | _aLast-mile delivery in cities, where the main problems are the traffic situation and ensuring access to customers’ homes while maintaining their privacy, poses a substantial logistical challenge. This book explores how the service area of mobility, especially last-mile delivery, can be improved and smartified. It demonstrates how a design science method and a transdisciplinary approach have been used to create a traffic area analysis tool that can accommodate the uncertainty and incompleteness of geospatial data; a linguistic traffic merging tool; and a customer classifier. In terms of developing the optimization artifacts, the socio-economic and logistical aspects of cities were considered and fuzzy logic and nature-inspired swarm intelligence (fuzzy ant colony optimization) were applied as basic principles. Pursuing a transdisciplinary approach, the book offers both practical know-how from the industry and theoretical findings, making it a valuable asset for researchers and practitioners in the fields of mobility and logistics. | ||
650 | 0 | _aBusiness information services. | |
650 | 0 | _aBusiness logistics. | |
650 | 0 | _aApplication software. | |
650 | 0 |
_aSoftware engineering _xManagement. |
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650 | 1 | 4 | _aBusiness Information Systems. |
650 | 2 | 4 | _aLogistics. |
650 | 2 | 4 | _aComputer and Information Systems Applications. |
650 | 2 | 4 | _aSoftware Management. |
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783031167034 |
776 | 0 | 8 |
_iPrinted edition: _z9783031167058 |
776 | 0 | 8 |
_iPrinted edition: _z9783031167065 |
830 | 0 |
_aFuzzy Management Methods, _x2196-4149 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-031-16704-1 |
912 | _aZDB-2-SCS | ||
912 | _aZDB-2-SXCS | ||
942 | _cSPRINGER | ||
999 |
_c174437 _d174437 |